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    This event is organized by CBRC with financial support from the KAUST Office of Sponsored Research

Xin Gao

Associate professor of computer science in the Computer, Electrical and Mathematical Sciences and Engineering Division at King Abdullah University of Science and Technology (KAUST), Saudi Arabia.

Biography

​Dr. Xin Gao is also a PI in the Computational Bioscience Research Center at KAUST and an adjunct faculty member at David R. Cheriton School of Computer Science at University of Waterloo, Canada. 
Prior to joining KAUST, he was a Lane Fellow at Lane Center for Computational Biology in School of Computer Science at Carnegie Mellon University, U.S.. He earned his bachelor degree in Computer Science in 2004 from Computer Science and Technology Department at Tsinghua University, China, and his Ph.D. degree in Computer Science in 2009 from David R. Cheriton School of Computer Science at University of Waterloo, Canada. 
Dr. Gao’s research interests are building computational models, developing machine learning techniques, and designing efficient and effective algorithms, with particular focus on applications to key open problems in structural biology, systems biology and synthetic biology. He has co-authored more than 120 research articles in the fields of bioinformatics, machine learning, and statistics. 

All sessions by Xin Gao

KEYNOTE LECTURE: A Novel Graph-Based Constant-Column Biclustering Method for Mining Growth Phenotype Data
12:00 PM

Growth phenotype profiling of genome-wide gene-deletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions.

Xin Gao

Associate professor of computer science in the Computer, Electrical and Mathematical Sciences and Engineering Division at King Abdullah University of Science and Technology (KAUST), Saudi Arabia.

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